Hacker Newsnew | past | comments | ask | show | jobs | submitlogin

Just include time in the model and use lagged features. It’s used all the time in automated time series forecasting.


This can tease out transfer entropy but still isn't identifying causal factors.

A common issue you find would be confounding. Then, because you haven't identified the latent connection, you may try to increase level A to have effect on output B, and be disappointed.

This is basically Judea Pearls Book of Why's main hypothesis, that E(Y|X) != E(Y|do(X)), where do(X) is when we modify X somehow.




Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: